Multi-walled carbon nanotube-supported Ni@Pd core–shell electrocatalyst for direct formate fuel cells

Journal of Applied Electrochemistry - In the present work, Ni@Pd core–shell nanoparticles are successfully deposited on multi-walled carbon nanotubes as support and investigated their...     

A High-Performance Solution-Processed Organic Photodetector for Near-Infrared Sensing

Sensitive detection of near-infrared (NIR) light enables many important applications in both research and industry. Current organic photodetectors suffer from low NIR sensitivity typically due to early absorption cutoff, low responsivity, and/or large dark/noise current under bias. Herein, organic photodetectors based on a novel ultranarrow-bandgap nonfullerene acceptor, CO1-4Cl, are presented, showcasing a remarkable responsivity over 0.5 A W⁻¹ in the NIR spectral region (920–960 nm), which is the highest among organic photodiodes. By effectively delaying the onset of the space charge limited current and suppressing the shunt leakage current, the optimized devices show a large specific detectivity around 10¹² Jones for NIR spectral region up to 1010 nm, close to that of a commercial Si photodiode. The presented photodetectors can also be integrated in photoplethysmography for real-time heart-rate monitoring, suggesting its potential for practical applications.     

Compactness of Protein Folds Alters Disulfide-Bond Reducibility by Three Orders of Magnitude: A Comprehensive Kinetic Case Study on the Reduction of Differently Sized Tryptophan Cage Model Proteins

A new approach to monitor disulfide-bond reduction in the vicinity of aromatic cluster(s) has been derived by using the near-UV range (λ=266–293 nm) of electronic circular dichroism (ECD) spectra. By combining the results from NMR and ECD spectroscopy, the 3D fold characteristics and associated reduction rate constants (k) of E19_SS, which is a highly thermostable, disulfide-bond reinforced 39-amino acid long exenatide mimetic, and its N-terminally truncated derivatives have been determined under different experimental conditions. Single disulfide bond reduction of the E19_SS model (with an 18-fold excess of tris(2-carboxyethyl)phosphine, pH 7, 37 °C) takes hours, which is 20–30 times longer than that expected, and thus, would not reach completion by applying commonly used reduction protocols. It is found that structural, steric, and electrostatic factors influence the reduction rate, resulting in orders of magnitude differences in reduction half-lives (900>t_1/2>1 min) even for structurally similar, well-folded derivatives of a small model protein.     

Thermoelectric properties of W1−xNbxSe2−ySy polycrystalline compounds

We investigate the thermoelectric properties of bulk polycrystalline samples of WSe₂-based compounds with partial substitutions in the cationic (W) and the anionic (Se) sublattices in the temperature range from 4.2 to 650 K. The substitution of W for Nb leads to a significant increase in the charge carrier concentration, however, deteriorates the charge carrier mobility. In contrast, the substitution of selenium for sulfur increases the charge carrier mobility, the thermal conductivity, and the Seebeck coefficient but conductivity changes non-monotonical. We show that the addition of sulfur in anionic sublattice affects the grain sizes in the polycrystalline material. Using substitutions in the anionic and cationic sublattices, we find the optimal ratio of the elements for better thermoelectric efficiency. The W_0.98Nb_0.02Se_1.7S_0.3 sample showed the best value of the figure of merit ZT = 0.26 (T = 650 K).     

Surface Topography and Optical Properties of Thin AlN Films Produced on GaAs (100) Substrate by Reactive Ion-Plasma Sputtering

Technical Physics Letters - A study of the surface topography and optical characteristics of thin AlN films used as passivating and antireflection coatings deposited on n-GaAs (100) substrates by...     

Properties of a single SnO2:Zn2SnO4 – Functionalized nanowire based nanosensor

Tin oxide nanowires (SnO₂ NWs) exhibit large potential for applications in sensor and detector technology. Using a flame transport synthesis method, high-quality single crystalline SnO₂ nanowires (NWs) with Zn₂SnO₄ dots functionalized surface were synthesized on a large scale. The individual SnO₂:Zn₂SnO₄ nanowire based ultraviolet photodetector and ethanol vapors nanosensors were fabricated by contacting an individual nanowire to pre-patterned Au electrodes via a FIB/SEM system. The photodetector structure exhibited excellent photoconductive performance in terms of high response to the 375 nm ultraviolet light irradiation, ultra-fast response and recovery time at different temperatures (25–300 K). It also showed a long term stability and reliability. The n-type semiconducting behavior of the SnO₂:Zn₂SnO₄, forms an excellent material for fabricating highly sensitive and rapid responding sensors, which will enable the development of high-performance multi-functional devices.     

Dynamic adaptation of online ensembles for drifting data streams

The success of data stream mining techniques has allowed decision makers to analyze their data in multiple domains, ranging from monitoring network intrusion to financial markets analysis and online sales transactions exploration. Specifically, online ensembles that construct accurate models against drifting data streams have been developed. Recently, there has been a surge in interest in mobile (or so-called pocket) data stream mining, aiming to construct near real-time models for data stream mining applications that run on mobile devices. In such a setting, it follows that the computational resources are limited and that there is a need to adapt analytics to map the resource usage requirements. Consequently, the resultant models should not only be highly accurate, but they should also adapt swiftly to changes. In addition, the data mining techniques should be fast, scalable, and efficient in terms of resource allocation. It then becomes important to consider Return on Investment (ROI) issues such as storage requirements and memory utilization. This paper introduces the Adaptive Ensemble Size (AES) algorithm, an extension of the Online Bagging method, to address these issues. Our AES method dynamically adapts the sizes of ensembles, based on ROI usage patterns. We illustrate our approach by analyzing the performances against both synthetic and real-world data streams. The results, when comparing our AES algorithm with the state-of-the-art, indicate that we are able to obtain a high Return on Investment (ROI) and to swiftly adapt to change, without compromising on the predictive accuracy.